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Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques
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Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers proposed an alternative method for sewer sediment accumulation calculation using predictive models harnessing multiple linear regression model (MLRM) and artificial neural network (ANN). AL-Thawra trunk sewer in Baghdad city is selected as a case study area; data from a survey done on this trunk is used in the modeling process. Results showed that MLRM is acceptable, with an adjusted coefficient of determination (adj. R2) in order of 89.55%. ANN model found to be practical with R2 of 82.3% and fit the data better throughout its range. Sensitivity analysis showed that the flow is the most influential parameter on the depth of sediment deposition.

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
(Structure Logistic Regression Model Of Anomalies Birth In Iraq Except Kurdistan Region, for 2015)
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Congenital anomalies commonly occur in humans, possibly visible. If these anomalies appear in visible parts in human body such as face, hands and feet. They may only appear after utilizing a number of special tests in order to show by means of the anomalies that occur in the internal organs of the body such as heart, stomach and kidneys.

    Research data have comprised accessible information in the anomalies birth statistics form situated of Health and Life Statistics section at the Ministry of Health and environment, where the number of anomalies births involved in the study (2603 anomalies birth) in Iraq, except Kurdistan region, at 2015. A two way-response logistic regression analysis h

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Publication Date
Tue Jul 01 2014
Journal Name
Ieee Transactions On Circuits And Systems I: Regular Papers
Crosstalk-Aware Multiple Error Detection Scheme Based on Two-Dimensional Parities for Energy Efficient Network on Chip
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Achieving reliable operation under the influence of deep-submicrometer noise sources including crosstalk noise at low voltage operation is a major challenge for network on chip links. In this paper, we propose a coding scheme that simultaneously addresses crosstalk effects on signal delay and detects up to seven random errors through wire duplication and simple parity checks calculated over the rows and columns of the two-dimensional data. This high error detection capability enables the reduction of operating voltage on the wire leading to energy saving. The results show that the proposed scheme reduces the energy consumption up to 53% as compared to other schemes at iso-reliability performance despite the increase in the overhead number o

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
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 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Solution of Fuzzy Maximal Flow Problems of Vehicles in Province of Diwaniyah Using the Ranking Function for Fuzzy Linear Programming Model
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Abstract

The traffic jams taking place in the cities of the Republic of Iraq in general and the province of Diwaniyah especially, causes return to the large numbers of the modern vehicles that have been imported in the last ten years and the lack of omission for old vehicles in the province, resulting in the accumulation of a large number of vehicles that exceed the capacity of the city's streets, all these reasons combined led to traffic congestion clear at the time of the beginning of work in the morning, So researchers chose local area network of the main roads of the province of Diwaniyah, which is considered the most important in terms of traffic congestion, it was identified  fuzzy numbers for

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Publication Date
Mon Nov 01 2010
Journal Name
Iraqi Journal Of Physics
New Technique for Treatment of the dust accumulation from PV solar panels surface
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One of the most important problems facing the world today is the energy problem. The solution was in finding renewable energy sources such as solar energy. The solar energy applications in Iraq is facing many problems . One of the most important problems is the accumulation of dust on the solar panels surface which causes decreasing its performance sharply. In the present work, a new technique was presented by using two-axis solar tracking system to reduce the accumulated dust on the solar panel surface and compared it with the fixed solar panels which installed at tilt angles 30° and 45°. The results indicated that the maximum losses of the output power due to accumulation of dust on the fixed solar panels is about 31.4% and 23.1% res

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Sat Dec 30 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Finite Element Neural Network And Its Applications To Forward And Inverse Problems
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In this paper, first we   refom1Ulated   the finite   element  model

(FEM)   into   a   neural   network   structure   using   a   simple   two   - dimensional problem. The structure of this neural network is described

, followed  by its   application   to   solving  the forward    and  inverse problems. This model is then extended to the general case and the advantages and  di sadvantages  of  this  approach  are  descri bed  along with an analysis  of  the sensi tivity   of

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Publication Date
Sat Oct 02 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors
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Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

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Publication Date
Fri Mar 04 2022
Journal Name
Environmental Science And Pollution Research
Geographically weighted regression model for physical, social, and economic factors affecting the COVID-19 pandemic spreading
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Abstract<p>This study aims to analyze the spatial distribution of the epidemic spread and the role of the physical, social, and economic characteristics in this spreading. A geographically weighted regression (GWR) model was built within a GIS environment using infection data monitored by the Iraqi Ministry of Health records for 10 months from March to December 2020. The factors adopted in this model are the size of urban interaction areas and human gatherings, movement level and accessibility, and the volume of public services and facilities that attract people. The results show that it would be possible to deal with each administrative unit in proportion to its circumstances in light of the factors that appe</p> ... Show More
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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Classic Local Least Estimatop And Bayesian Methoid For Estimating Semiparametric Logistic Regression Model
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Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

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